Abstract B018: Gut microbiome influences the antitumor response to BCG immunotherapy in bladder cancer
Bibliographic record
Abstract
Abstract Introduction: Bacillus Calmette-Guérin (BCG) intravesical immunotherapy remains the standard treatment for non-muscle-invasive bladder cancer (NMIBC). Unfortunately, up to 40% of patients experience disease recurrence. Emerging evidence suggests that gut microbiome composition and function influence responses to systemic immunotherapies. Here, we investigated the impact of the gut microbiota on the antitumor efficacy of BCG in NMIBC patients and avatar mouse models. Methods: We prospectively collected fecal samples from 58 NMIBC patients prior to BCG therapy initiation and profiled their gut microbiome composition using 16S rRNA sequencing and whole shotgun metagenomics. Targeted metabolites from feces and patient serum were analyzed using GC-FID. To assess causality, fecal microbiota transplantation (FMT) from responders (R; n=42) and non-responders (NR; n=16) was performed into gut microbiota-depleted MBT-2 tumor-bearing mice, followed by weekly intratumoral BCG treatment. Bulk RNA sequencing of tumors was performed to elucidate the molecular mechanisms. To test the biological activity of specific bacterial strains identified from R patients, NR avatar mice were supplemented with the bacterial consortium. The immune-potentiating effect of this consortium on BCG activity was evaluated using flow cytometry. The immunogenic activity of bacterial strains was further assessed by IFN-γ ELISpot assays on splenocytes. Results: Differential abundance analysis of gut microbiome between R and NR patients identified nine taxa enriched in R. Stratifying patients by median abundance of each taxon revealed that a higher abundance of three bacteria was significantly associated with prolonged recurrence-free survival (RFS). FMT from NR patients reduced BCG efficacy compared to R patients. Metabolomic analysis identified one specific SCFA enriched in R patients, which was also elevated in the cecum of R-avatar mice. Flow cytometry analysis from R- vs. NR-avatar mice showed that FMT from R patients increased IFN-γ+CD8+ T cells and reduced TAMs and MDSCs in the tumor microenvironment, supported by RNA sequencing data showing an enrichment of IFN-γ and TNF-α signaling pathways in tumors. Oral supplementation of NR-recipient mice with the R-associated bacterial consortium restored the BCG efficacy. This was accompanied by increased CD3+ T cells in mLNs, elevated IFN-γ+ CD4+ and CD8+ T cells, and a reduction in PD-L1+ myeloid cells in spleen and tumor. ELISpot showed increased IFN-γ production in response to the bacterial strains, supporting an immunogenic potential and synergistic activity with BCG immunotherapy. Conclusions: Our findings demonstrate that gut microbiome influences the response to BCG immunotherapy in NMIBC patients. This study paves the way for microbiome-targeted strategies such as bacterial supplementation or metabolite-based interventions to enhance the efficacy of BCG treatment in bladder cancer. Citation Format: Jalal Laaraj, Gabriel Lachance, Prisca Nadège. Koné, Roxane Tourigny, Typhaine Gris, Paul Toren, Alain Bergeron, Sandra Isabel, Yves Fradet, Karine Robitaille, Vincent Fradet. Gut microbiome influences the antitumor response to BCG immunotherapy in bladder cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr B018.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".